Hessam Babaee

The research areas of interest to our lab are at the interface of scientific computing and machine learning. In particular, we develop data-driven and model-driven reduced order modeling techniques to reduce the computational cost of solving a variety of problems. This includes uncertainty quantification, high-dimensional sensitivity analysis, passive and reactive species transport and high-dimensional probability density function transport equations that arise in a number of scientific and engineering problems.We focus on a diverse set of applications from fluid dynamics and bioengineering to ocean engineering.

  • Co-PI of Wireless Underwater Power Transfer for AUVs: Optimization via Metamaterials funded by NOAA.
  • PI of XSEDE supercomputer allocation of 4.6 million SU’s for Developing Stochastic Reduced-Order Models for Thermal Components, funded by NSF.
  • PI of XSEDE supercomputer allocation of 1.1 million SU’s for Developing Stochastic Reduced-Order Models for Thermal Components, funded by NSF.
  • First place poster presentation 2010-Mechanical Engineering graduate student conference, Louisiana State University.

  • Ph.D. in Mechanical Engineering, Louisiana State University, 2013
  • M.Sc. in Applied Mathematics, Louisiana State University, 2013
  • M.Sc. in Mechanical Engineering, University of Tehran, 2006
  • B.Sc. in Mechanical Engineering, University of Tehran, 2003

  • Zhang, P., Naeem, K., Babaee, H., Venketeswaran, A., Sarcinelli, E., Bukka, S.R., Lalam, N., Wright, R., & Ohodnicki, P.R. (2026). Reduced-Order Model Enhanced Progressive Domain Adversarial Network: Synthetic-to-Real Ultrasonic Defect Detection Using Fiber Optic Guided Wave Data. In Elsevier BV. doi: 10.2139/ssrn.6232709.
  • Aitzhan, A., Givi, P., & Babaee, H. (2025). On-the-fly reduced-order modelling of the filter density function with time-dependent subspaces. COMBUSTION THEORY AND MODELLING, 29(3), 359-377.Taylor & Francis. doi: 10.1080/13647830.2025.2492571.
  • Aitzhan, A., Nouri, A.G., Givi, P., & Babaee, H. (2025). Reduced order modeling of turbulent reacting flows on low-rank matrix manifolds. JOURNAL OF COMPUTATIONAL PHYSICS, 521.Elsevier. doi: 10.1016/j.jcp.2024.113549.
  • Akhavan, S., Sridar, S., Babaee, H., & Xiong, W. (2025). Multi-fidelity framework and uncertainty quantification for thermal conductivities of aluminum alloys. JOURNAL OF APPLIED PHYSICS, 138(5).AIP Publishing. doi: 10.1063/5.0277770.
  • Jung, K.S., Lacey, C.E., Babaee, H., & Chen, J.H. (2025). Accelerating high-fidelity simulations of chemically reacting flows using reduced-order modeling with time-dependent bases. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 437.Elsevier. doi: 10.1016/j.cma.2025.117758.
  • Liu, Y., Babaee, H., Givi, P., Livescu, D., & Nouri, A.G. (2025). On-the-fly reduced-order modelling for skeletal reduction of gasoline surrogate combustion. COMBUSTION THEORY AND MODELLING, 29(7), 840-853.Taylor & Francis. doi: 10.1080/13647830.2025.2567377.
  • Naderi, M.H., Akhavan, S., & Babaee, H. (2025). A cross algorithm for implicit time integration of random partial differential equations on low-rank matrix manifolds. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 481(2309).The Royal Society. doi: 10.1098/rspa.2024.0658.
  • Sridar, S., Xiong, W., Babaee, H., Fahrenholtz, W., & McCormack, S.J. (2025). Uncertainty quantification of materials processing for ultrahigh-temperature materials. AMERICAN CERAMIC SOCIETY BULLETIN, 104(2).
  • Zhong, Y., Amiri-Margavi, A., Babaee, H., & Taira, K. (2025). Optimally time-dependent modes of vortex gust-airfoil interactions. JOURNAL OF FLUID MECHANICS, 1006.Cambridge University Press (CUP). doi: 10.1017/jfm.2025.9.
  • Amiri-Margavi, A., & Babaee, H. (2024). Time-dependent low-rank input-output operator for forced linearized dynamics with unsteady base flows. JOURNAL OF FLUID MECHANICS, 1001.Cambridge University Press (CUP). doi: 10.1017/jfm.2024.1019.
  • Ashtiani, S.Z., Sarabian, M., Laksari, K., & Babaee, H. (2024). Reconstructing blood flow in data-poor regimes: a vasculature network kernel for Gaussian process regression. J R Soc Interface, 21(217), 20240194.The Royal Society. doi: 10.1098/rsif.2024.0194.
  • Ghahremani, B., & Babaee, H. (2024). Cross interpolation for solving high-dimensional dynamical systems on low-rank Tucker and tensor train manifolds. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 432.Elsevier. doi: 10.1016/j.cma.2024.117385.
  • Ghahremani, B., & Babaee, H. (2024). A DEIM Tucker tensor cross algorithm and its application to dynamical low-rank approximation. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 423.Elsevier. doi: 10.1016/j.cma.2024.116879.
  • Goswami, S., Jagtap, A.D., Babaee, H., Susi, B.T., & Karniadakis, G.E. (2024). Learning stiff chemical kinetics using extended deep neural operators. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 419.Elsevier. doi: 10.1016/j.cma.2023.116674.
  • Nouri, A.G., Liu, Y., Givi, P., Babaee, H., & Livescu, D. (2024). Skeletal Kinetics Reduction for Astrophysical Reaction Networks. ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES, 272(2).American Astronomical Society. doi: 10.3847/1538-4365/ad454a.
  • Donello, M., Palkar, G., Naderi, M.H., Del Rey Fernandez, D.C., & Babaee, H. (2023). Oblique projection for scalable rank-adaptive reduced-order modelling of nonlinear stochastic partial differential equations with time-dependent bases. PROCEEDINGS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 479(2278).The Royal Society. doi: 10.1098/rspa.2023.0320.
  • Liu, Y., Babaee, H., Givi, P., Chelliah, H.K., Livescu, D., & Nouri, A.G. (2023). Skeletal reaction models for methane combustion. FUEL, 357.Elsevier. doi: 10.1016/j.fuel.2023.129581.
  • Naderi, M.H., & Babaee, H. (2023). Adaptive sparse interpolation for accelerating nonlinear stochastic reduced-order modeling with time-dependent bases. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 405.Elsevier. doi: 10.1016/j.cma.2022.115813.
  • Patil, P., & Babaee, H. (2023). Reduced-Order Modeling with Time-Dependent Bases for PDEs with Stochastic Boundary Conditions. SIAM-ASA JOURNAL ON UNCERTAINTY QUANTIFICATION, 11(3), 727-756.Society for Industrial & Applied Mathematics (SIAM). doi: 10.1137/21M1468097.
  • Ashtiani, S.Z., Malik, M.R., & Babaee, H. (2022). Scalable in situ compression of transient simulation data using time-dependent bases. JOURNAL OF COMPUTATIONAL PHYSICS, 468.Elsevier. doi: 10.1016/j.jcp.2022.111457.
  • Donello, M., Carpenter, M.H., & Babaee, H. (2022). COMPUTING SENSITIVITIES IN EVOLUTIONARY SYSTEMS: A REAL-TIME REDUCED ORDER MODELING STRATEGY. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 44(1), A128-A149.Society for Industrial & Applied Mathematics (SIAM). doi: 10.1137/20M1388565.
  • Gourianov, N., Lubasch, M., Dolgov, S., van den Berg, Q.Y., Babaee, H., Givi, P., Kiffner, M., & Jaksch, D. (2022). A quantum-inspired approach to exploit turbulence structures. Nat Comput Sci, 2(1), 30-37.Springer Nature. doi: 10.1038/s43588-021-00181-1.
  • Sarabian, M., Babaee, H., & Laksari, K. (2022). Physics-Informed Neural Networks for Brain Hemodynamic Predictions Using Medical Imaging. IEEE Trans Med Imaging, 41(9), 2285-2303.Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/TMI.2022.3161653.
  • Meng, X., Babaee, H., & Karniadakis, G.E. (2021). Multi-fidelity Bayesian neural networks: Algorithms and applications. JOURNAL OF COMPUTATIONAL PHYSICS, 438.Elsevier. doi: 10.1016/j.jcp.2021.110361.
  • Ramezanian, D., Nouri, A.G., & Babaee, H. (2021). On-the-fly reduced order modeling of passive and reactive species via time-dependent manifolds. COMPUTER METHODS IN APPLIED MECHANICS AND ENGINEERING, 382.Elsevier. doi: 10.1016/j.cma.2021.113882.
  • Arrué, P., Toosizadeh, N., Babaee, H., & Laksari, K. (2020). Low-Rank Representation of Head Impact Kinematics: A Data-Driven Emulator. Front Bioeng Biotechnol, 8, 555493.Frontiers. doi: 10.3389/fbioe.2020.555493.
  • Babaee, H., Bastidas, C., DeFilippo, M., Chryssostomidis, C., & Karniadakis, G.E. (2020). AMultifidelity Framework and Uncertainty Quantification for Sea Surface Temperature in the Massachusetts and Cape Cod Bays. EARTH AND SPACE SCIENCE, 7(2).American Geophysical Union (AGU). doi: 10.1029/2019EA000954.
  • Patil, P., & Babaee, H. (2020). Real-time reduced-order modeling of stochastic partial differential equations via time-dependent subspaces. JOURNAL OF COMPUTATIONAL PHYSICS, 415.Elsevier. doi: 10.1016/j.jcp.2020.109511.
  • Babaee, H. (2019). An observation-driven time-dependent basis for a reduced description of transient stochastic systems. Proc Math Phys Eng Sci, 475(2231), 20190506.The Royal Society. doi: 10.1098/rspa.2019.0506.
  • Raissi, M., Babaee, H., & Givi, P. (2019). Deep learning of turbulent scalar mixing. PHYSICAL REVIEW FLUIDS, 4(12).American Physical Society (APS). doi: 10.1103/PhysRevFluids.4.124501.
  • Raissi, M., Babaee, H., & Karniadakis, G.E. (2019). Parametric Gaussian process regression for big data. COMPUTATIONAL MECHANICS, 64(2), 409-416.Springer Nature. doi: 10.1007/s00466-019-01711-5.
  • Laksari, K., Kurt, M., Babaee, H., Kleiven, S., & Camarillo, D. (2018). Mechanistic Insights into Human Brain Impact Dynamics through Modal Analysis. Phys Rev Lett, 120(13), 138101.American Physical Society (APS). doi: 10.1103/PhysRevLett.120.138101.
  • Zhang, D., Babaee, H., & Karniadakis, G.E. (2018). STOCHASTIC DOMAIN DECOMPOSITION VIA MOMENT MINIMIZATION. SIAM JOURNAL ON SCIENTIFIC COMPUTING, 40(4), A2152-A2173.Society for Industrial & Applied Mathematics (SIAM). doi: 10.1137/17M1160756.
  • Babaee, H., Choi, M., Sapsis, T.P., & Karniadakis, G.E. (2017). A robust bi-orthogonal/dynamically-orthogonal method using the covariance pseudo-inverse with application to stochastic flow problems. JOURNAL OF COMPUTATIONAL PHYSICS, 344, 303-319.Elsevier. doi: 10.1016/j.jcp.2017.04.057.
  • Babaee, H., Farazmand, M., Haller, G., & Sapsis, T.P. (2017). Reduced-order description of transient instabilities and computation of finite-time Lyapunov exponents. Chaos, 27(6), 063103.AIP Publishing. doi: 10.1063/1.4984627.
  • Babaee, H., & Sapsis, T.P. (2016). A minimization principle for the description of modes associated with finite-time instabilities. Proc Math Phys Eng Sci, 472(2186), 20150779.The Royal Society. doi: 10.1098/rspa.2015.0779.
  • Babaee, H., Perdikaris, P., Chryssostomidis, C., & Karniadakis, G.E. (2016). Multi-fidelity modelling of mixed convection based on experimental correlations and numerical simulations. JOURNAL OF FLUID MECHANICS, 809, 895-917.Cambridge University Press (CUP). doi: 10.1017/jfm.2016.718.
  • Alvergue, L., Babaee, H., Gu, G., & Acharya, S. (2015). Feedback Stabilization of a Reduced-Order Model of a Jet in Crossflow. AIAA JOURNAL, 53(9), 2472-2481.American Institute of Aeronautics and Astronautics (AIAA). doi: 10.2514/1.J053295.
  • Zheng, X., Babaee, H., Dong, S., Chryssostomidis, C., & Karniadakis, G.E. (2015). A phase-field method for 3D simulation of two-phase heat transfer. INTERNATIONAL JOURNAL OF HEAT AND MASS TRANSFER, 82, 282-298.Elsevier. doi: 10.1016/j.ijheatmasstransfer.2014.11.052.
  • Babaee, H., & Acharya, S. (2014). A HYBRID STAGGERED/SEMISTAGGERED FINITE-DIFFERENCE ALGORITHM FOR SOLVING TIME-DEPENDENT INCOMPRESSIBLE NAVIER-STOKES EQUATIONS ON CURVILINEAR GRIDS. NUMERICAL HEAT TRANSFER PART B-FUNDAMENTALS, 65(1), 1-26.Taylor & Francis. doi: 10.1080/10407790.2013.827012.
  • Babaee, H., Acharya, S., & Wan, X. (2014). Optimization of Forcing Parameters of Film Cooling Effectiveness. JOURNAL OF TURBOMACHINERY-TRANSACTIONS OF THE ASME, 136(6).ASME International. doi: 10.1115/1.4025732.
  • Babaee, H., Wan, X., & Acharya, S. (2014). Effect of Uncertainty in Blowing Ratio on Film Cooling Effectiveness. JOURNAL OF HEAT TRANSFER-TRANSACTIONS OF THE ASME, 136(3).ASME International. doi: 10.1115/1.4025562.

  • Zhong, Y., Amiri-Margavi, A., Babaee, H., & Taira, K. (2024). Transient Perturbation Dynamics of Vortex-Airfoil Interaction. In AIAA AVIATION FORUM AND ASCEND 2024.American Institute of Aeronautics and Astronautics (AIAA). doi: 10.2514/6.2024-4110.
  • Nouri, A.G., Babaee, H., Givi, P., Chelliah, H.K., & Livescu, D. (2022). Skeletal model reduction with forced optimally time dependent modes. In COMBUSTION AND FLAME, 235.Elsevier.College Station, TX. doi: 10.1016/j.combustflame.2021.111684.
  • Zhang, P., Venketeswaran, A., Wright, R., Denslow, K., Babaee, H., & Ohodnicki, P.R. (2022). Feature extraction for pipeline defects inspection based upon distributed acoustic fiber optic sensing data. In Sanders, G.A., Lieberman, R.A., & Scheel, I.U. (Eds.). In Proceedings of SPIE--the International Society for Optical Engineering, 12105, (p. 1210503-1210503-16).SPIE, the international society for optics and photonics. doi: 10.1117/12.2618263.
  • Wang, Z., Karniadakis, G.E., Chalfant, J., Chryssostomidis, C., & Babaee, H. (2017). High-Fidelity Modeling and Optimization of Conjugate Heat Transfer in Arrays of Heated Cables. In 2017 IEEE Electric Ship Technologies Symposium (ESTS), (pp. 557-563).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ests.2017.8069337.
  • Babaee, H., Chalfant, J., Chryssostomidis, C., & Sanfiorenzo, A.B. (2015). System-Level Analysis of Chilled Water Systems Aboard Naval Ships. In 2015 IEEE Electric Ship Technologies Symposium (ESTS), (pp. 370-375).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ests.2015.7157921.
  • Yang, S., Ordonez, J.C., Vargas, J.V.C., Babaee, H., Chalfant, J., & Chryssostomidis, C. (2015). Comprehensive System-Level Thermal Modeling of All-Electric Ships: Integration of SMCS and Vemesrdc. In 2015 IEEE Electric Ship Technologies Symposium (ESTS), (pp. 251-255).Institute of Electrical and Electronics Engineers (IEEE). doi: 10.1109/ests.2015.7157898.
  • Babaee, H., Acharya, S., & Wan, X. (2013). Optimization of Forcing Parameters of Film Cooling Effectiveness. In Volume 3B: Heat Transfer, 3, (p. v03bt13a055).ASME International. doi: 10.1115/gt2013-95636.
  • Babaee, H., Wan, X., & Acharya, S. (2013). Effect of Uncertainty in Blowing Ratio on Film Cooling Effectiveness. In Volume 3: Gas Turbine Heat Transfer; Transport Phenomena in Materials Processing and Manufacturing; Heat Transfer in Electronic Equipment; Symposium in Honor of Professor Richard Goldstein; Symposium in Honor of Prof. Spalding; Symposium in Honor of Prof. Arthur E. Bergles, 3, (p. v003t20a002).ASME International. doi: 10.1115/ht2013-17159.
  • Babaee, H., & Acharya, S. (2012). A Symmetric Finite Difference Discretization of Pressure-Poisson Equation on Curvilinear Grids. In 42nd AIAA Fluid Dynamics Conference and Exhibit 2012.American Institute of Aeronautics and Astronautics (AIAA). doi: 10.2514/6.2012-3068.
  • Babaee, H., & Acharya, S. (2012). A Symmetric Finite Difference Discretization of Pressure-Poisson Equation on Curvilinear Grids. In 42nd AIAA Fluid Dynamics Conference and Exhibit.American Institute of Aeronautics and Astronautics. doi: 10.2514/6.2012-3068.
  • Babaee, H., & Acharya, S. (2011). A Semi-Staggered Numerical Procedure for the Incompressible Navier-Stokes Equations on Curvilinear Grids. In Volume 6: Fluids and Thermal Systems; Advances for Process Industries, Parts A and B, 6(PARTS A AND B), (pp. 927-936).ASME International. doi: 10.1115/imece2011-64224.
Research Interests
Fluid mechanics and thermal engineering Applied mathematics Aerospace engineering Mechanical engineering Biomedical engineering Chemical engineering